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Agritech & Spatial Data: Predicting Crop Yield in Rural Australia

This post was written by NGIS, our master reseller in Australia and New Zealand and was originally published on their website.

Building Rural Intelligence For The Agricultural Sector

Digital Agriculture Services (DAS) is an Australian rural technology company that was established in a partnership with Commonwealth Scientific and Industrial Research Organisation (CSIRO) to help assess, value, and monitor rural assets used in digital agriculture.

DAS’ Rural Intelligence platform is a hub that holds over 25 data sources for 1.2 million paddocks across Australia. The data available on the platform includes rainfall, soil type, property information, paddock sizes, and more. These data sources are collated and combined with individual business data to provide rural intelligence about properties, developments, and farm land.

After speaking to stakeholders, the DAS team identified a need for gaining insights on crop yield and historical data across Australia. The DAS team engaged NGIS to build a spatial web application, known as the CroppingHub, that used cloud computing and machine learning to detect crop types and predict crop yield based on historical data and CSIRO science.

Stakeholders Require Fast And Accurate Data

In the agricultural industry, external stakeholders that work in trading, bulk handling, insurance, banking and retail require spatial information and historical crop data to answer questions such as:

  • What crops are growing where?
  • What is the expected production of major crop types?
  • How do growing season conditions and forecast production compare to previous seasons at the National, State and Local Government levels?

The DAS team had the data, vision, and design capabilities to answer these questions, but needed the assistance of a trusted partner to provide the spatial elements of the solution to improve its presentation, speed, and accuracy. This was the beginning of what would eventually become the DAS CroppingHub.

Working with the NGIS team was a pleasure, the team was efficient, flexible, knowledgeable and provided a quick turnaround for any issues that came up during the project.
Sagit Shiran, Head Of Product At Digital Agriculture Services (DAS).

Classifying Crops And Yield Prediction Across Australia

NGIS worked closely with the DAS team to build out the CroppingHub prototype application that matched their designs and user stories. CroppingHub provides insights across Australia’s winter cropping regions, giving users current statistics and historical context to help make informed and accurate decisions.

Using Google Earth Engine, CroppingHub can classify what crop is growing in every paddock in Australia, and then apply a proprietary yield prediction algorithm developed by CSIRO to CroppingHub’s vector dataset of over 1.2 million paddocks. These data are summarised by State and Local Government Areas to provide DAS clients with more accurate crop information.

The web application, built on CARTO Engine and hosted on Google Cloud, enables the DAS team to update the data at high frequency to ensure clients have the most up to date information possible.

Further, the data that exists today on the CroppingHub platform can be imported into the Rural Intelligence app – so it becomes another data source that the team can use.

Screenshot of DAS CroppingHub

Transforming The Future Of Farming Business

CroppingHub has enabled the DAS team to take future steps together with their customers, ultimately transforming how different businesses operate and trade within the agricultural sector.

Since deployment of CroppingHub, the DAS team can continue to improve the accuracy of the provided data and work with customers and prospects in a very transparent manner to improve grain traders, marketers and other agribusinesses decision-making.

This was a first successful iteration and now we can engage in many more conversations and build on top of an existing solution.
Sagit Shiran, Head Of Product At Digital Agriculture Services (DAS).

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Jaimee Nobbs

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